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Moiré Fringe Segmentation Using Fuzzy Inference System

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9th International Conference on Robotic, Vision, Signal Processing and Power Applications

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 398))

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Abstract

The analysis of geometric moiré patterns is always carried out using image processing techniques and computational methods. Good segmentation of moiré fringes is desirable to reduce the uncertainty in moiré pattern analysis. In this work, a moiré fringes segmentation approach based on a fuzzy inference system (FIS) is proposed. Feature selection based on amplitude parameters and the construction of the FIS for the segmentation are described. An average recognition rate of 81.17 % is recorded for moiré fringe detection using FIS. Qualitative comparison of the moiré patterns before and after segmentation is made to confirm the applicability of the FIS-based segmentation approach.

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Author information

Authors and Affiliations

  1. School of Mechanical Engineering, Engineering Campus, Universiti Sains Malaysia, 14300, Nibong Tebal, Penang, Malaysia

    Wing Hon Woo & Kin Sam Yen

Authors
  1. Wing Hon Woo
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  2. Kin Sam Yen
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Corresponding author

Correspondence to Kin Sam Yen .

Editor information

Editors and Affiliations

  1. School of Electrical and Electronic Engineering, Universiti Sains Malaysia, Nibong Tebal, Penang, Malaysia

    Haidi Ibrahim

  2. School of Electrical & Electronic Engineering, Universiti Sains Malaysia, Nibong Tebal, Penang, Malaysia

    Shahid Iqbal

  3. School of Electrical & Electronic Engineering, Universiti Sains Malaysia, Nibong Tebal, Penang, Malaysia

    Soo Siang Teoh

  4. School of Electrical & Electronic Engineering, Universiti Sains Malaysia, Nibong Tebal, Penang, Malaysia

    Mohd Tafir Mustaffa

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© 2017 Springer Science+Business Media Singapore

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Woo, W.H., Yen, K.S. (2017). Moiré Fringe Segmentation Using Fuzzy Inference System. In: Ibrahim, H., Iqbal, S., Teoh, S., Mustaffa, M. (eds) 9th International Conference on Robotic, Vision, Signal Processing and Power Applications. Lecture Notes in Electrical Engineering, vol 398. Springer, Singapore. https://doi.org/10.1007/978-981-10-1721-6_27

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  • DOI: https://doi.org/10.1007/978-981-10-1721-6_27

  • Published:

  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-1719-3

  • Online ISBN: 978-981-10-1721-6

  • eBook Packages: EngineeringEngineering (R0)

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